The advent of cloud-based computing architectures has opened new possibilities for the rapid and scalable deployment of virtual Web stores, media outlets, social networking sites, and many other on-line sites or services. In general, a cloud-based architecture deploys a set of hosted resources such as processors, operating systems, software and other components that can be combined together to form virtual machines. A user or customer can request the instantiation of a virtual machine or set of machines from those resources from a central server or cloud management system to perform intended tasks, services, or applications. For example, a user may wish to set up and instantiate a virtual server from the cloud to create a storefront to market products or services on a temporary basis, for instance, to sell tickets to or merchandise for an upcoming sports or musical performance. The user can subscribe to the set of resources needed to build and run the set of instantiated virtual machines on a comparatively short-term basis, such as hours or days, for their intended application.
Typically, when a user utilizes a cloud, the user must track the software applications executed in the cloud and/or processes instantiated in the cloud. For example, the user must track the cloud processes to ensure that the correct cloud processes have been instantiated, that the cloud processes are functioning properly and/or efficiently, that the cloud is providing sufficient resources to the cloud processes, and so forth. Due in part to the user's requirements and overall usage of the cloud, the user may have many applications and/or processes instantiated in a cloud at any given instant, and the user's deployment of virtual machines, software, and other resources can change dynamically over time. In cases, the user may also utilize multiple independent clouds to support the user's cloud deployment. That user may further instantiate and use multiple applications or other software or services inside or across multiple of those cloud boundaries, and those resources may be used or consumed by multiple or differing end-user groups in those different cloud networks.
In terms of the procurement of processor, memory, storage, and/or other resources required to support one or more sets of users, the cloud management system of a set of host clouds may locate and install or provide those resources on a subscription, marketplace, and/or other basis. For users whose resource demands demonstrates a timer-dependent pattern, such as a relaxation of resource consumption during overnight, offpeak, and other hours or periods, it could be advantageous to time or predict the need to procure resources based on known consumption behavior. In aspects, a cloud operator could scale down or otherwise adjust the resources procured from a set of cloud resource servers if service level needs are known or could be predicted in advance, permitting potentially lower cost, reduced storage needs, decreased failover or rollover capacity, and/or otherwise altered configurations of the resources needed to support users in the operator's set of host clouds. It may be desirable to provide systems and methods for brokering optimized resource supply costs in a host cloud-based network using predictive workloads, in which workloads of users can be predictively re-assigned or shifted to leverage advantageous cloud support conditions in varying resource servers, based on estimated support requirements or levels in predetermined time periods.